Browse > Article
http://dx.doi.org/10.21219/jitam.2017.24.4.093

Using Choice-Based Conjoint Analysis to Determine Smartphone Choice - a Student's Perspective  

Baganzi, Ronald (Business Administration at the School of Management, Kyung Hee University)
Shin, Geon-Cheol (Marketing and Business Strategy at the School of Management, Kyung Hee University)
Wu, Shali (Marketing at the School of Management at Kyung Hee University)
Publication Information
Journal of Information Technology Applications and Management / v.24, no.4, 2017 , pp. 93-115 More about this Journal
Abstract
The ability of smartphones to facilitate various services like mobile banking, e-commerce and mobile payments has made them part of consumers' lives. Conjoint analysis (CA) is a marketing research approach used to assess how consumers' preferences for products or services develop. The potential applications of CA are numerous in consumer electronics, banking and insurance services, job selection and workplace loyalty, consumer packaged goods, and travel and tourism. Choice-Based Conjoint (CBC) analysis is the most commonly used CA approach in marketing research. The purpose of this study is to utilise CBC analysis to investigate the relative importance of smartphone attributes that influence consumer smartphone preference. An experiment was designed using Sawtooth CBC Software. 326 students attempted the online survey. Utility values were derived by Hierarchical Bayes (HB) estimation and used to explain consumers' smartphone preferences. All the six attributes used for the study were found to significantly influence smartphone preference. Smartphone brand was the most important, followed by the price, camera, RAM, battery life, and storage. This study is one of the first to use Sawtooth CBC analysis to assess consumer smartphone preference based on the six attributes. We provide implications for the development of new smartphones based on attributes.
Keywords
Conjoint Analysis; Consumer Preference; Hierarchical Bayes Model; Part-worth Utility; Smartphones;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Erdem, T. and Keane, M. P., "Decisionmaking Under Uncertainty : Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets", Marketing Science, Vol. 15, No. 1, 1996, pp. 1-20.   DOI
2 Garver, M.S ., Divine, R. L., and Spralls, S. A., "Choice-Based Conjoint Analysis of the Local Coupon Preferences of Millennials", Journal of Promotion Management, Vol. 20, No. 2, 2014, pp. 240-249.   DOI
3 Gibbs, S. and Yuhas, A., Samsung Suspends Sales of Galaxy Note 7 After Smartphones Catch Fire, Theguardian, 2016, Available at : https://www.theguardian.com/technology/ 2016/sep/02/samsung-recall-galaxynote- 7-reports-of-smartphones-catchingfire (accessed 20 March 2017).
4 Green, P. E. and Rao, V. R., "Conjoint Measurement for Quantifying Judgmental Data", Journal of Marketing Research, Vol. 8, No. 3, 1971, pp. 355-363.   DOI
5 Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E., Multivariate Data Analysis, New Intern., Pearson, London, 2014.
6 Halme, M. and Kallio, M., "Estimation methods for choice-based conjoint analysis of consumer preferences", European Journal of Operational Research, Vol. 214, No. 1, 2011, pp. 160-167.   DOI
7 Head, M. and Ziolkowski, N., "Understanding student attitudes of mobile phone features : Rethinking adoption through conjoint, cluster and SEM analyses", Computers in Human Behavior, Vol. 28, No. 6, 2012, pp. 2331-2339.   DOI
8 Zwerina, K., Huber, J., and Kuhfeld, W. F., A General Method for Constructing Efficient Choice Designs, Durham, NC : Fuqua School of Business, Duke University, 1996, Available at : http://citeseerx.ist.psu.edu/viewdoc/ download?doi=10.1.1.31.9438&rep=rep1&ty pe=pdf (accessed 10 April 2017).
9 Dey, A., Orthogonal Fractional Factorial Designs, Halstead Press, New York, 1985.
10 International Data Corporation., Smartphone Vendor Market Share, 2017 Q1, International Data Corporation, 2017, Available at : https://www.idc.com/promo/smartphonemar ket-share/vendor (accessed 30 November 2017).
11 Karjaluoto, H., Karvonen, J., Kesti, M., Koivumaki, T., Manninen, M., Pakola, J., Ristola, A., et al., "Factors Affecting Consumer Choice of Mobile Phones: Two Studies from Finland", Journal of Euro Marketing, Vol. 14, No. 3, 2005, pp. 59-82.
12 Jervis, S., Ennis, J., and Drake, M., "A Comparison of Adaptive Choice-Based Conjoint and Choice-Based Conjoint to Determine Key Choice Attributes of Sour Cream with Limited Sample Size", Journal of Sensory Studies, Vol. 27, No. 6, 2012, pp. 451-462.   DOI
13 Jung, Y.-H. and Kim, S.-C., "Response to potential information technology risk : Users' valuation of electromagnetic field from mobile phones", Telematics and Informatics, Vol. 32, No. 1, 2014, pp. 57-66.   DOI
14 Kabadayi, E., Alan, A., and Ozkan, B., "Effects of Product Properties on Consumer Preferences and Behaviours : A Study of the Automobile Market in Turkey", International Journal of Management, Vol. 30, No. 1, 2013, pp. 349-362.
15 Kim, D.-J., Chun, H.-S., and Lee, H.-J., "Determining the Factors that Influence College Students' Adoption of Smartphones", Journal of the Association for Information Science and Technology, Vol. 65, No. 3, 2014, pp. 578-588.   DOI
16 Lee, S.-H., "How hotel managers decide to discount room rates: A conjoint analysis", International Journal of Hospitality Management, Vol. 52, No. 1, 2016, pp. 68-77.   DOI
17 Kim, J. S., "Empirical Analysis of Consumer Willingness To Pay for Smart Phone Attributes in Multi-Countries", International Journal of Innovation Management, Vol. 21, No. 2, 2016, Available at : https://doi.org/10.1142/ S1363919617500165.   DOI
18 Kim, M.-K., Wong, S.-F., Chang, Y.-H., and Park, J.-H., "Determinants of customer loyalty in the Korean smartphone market : Moderating effects of usage characteristics", Telematics and Informatics, Elsevier Ltd, Vol. 33, No. 4, 2016, pp. 936-949.   DOI
19 Kuzmanovic, M., Gusavac, B., and Martic, M., "Using Conjoint Analysis to Identify Key Factors Influencing Customer Value", Technics Technologies Education Management, Vol. 7, No. 4, 2012, pp. 1699-1706.
20 Lee, J.-H., Kim, D.-W., and Zo, H.-J., "Conjoint analysis on preferences of HRD managers and employees for effective implementation of m-learning : The case of South Korea", Telematics and Informatics, Elsevier Ltd, Vol. 32, No. 4, 2015, pp. 940-948.   DOI
21 Li, M. and Shuai, Z., "The Effects of Countyof- Origin, Brand Image, and Corporate Image Dimensions on Brand Evaluations and Purchase Intentions of Smartphones of Five Brands : A Comparative Study of China and Korea", Journal of Distribution Science, Vol. 11, No. 7, 2013, pp. 47-56.   DOI
22 Louviere, J. J., Hensher, D. and Swait, J., Stated Choice Methods : Analysis and Application, Cambridge University Press, Cambridge, 2000.
23 McDaniel, C. and Gates, R., Marketing Research, 9th ed., Wiley, Hoboken, NJ, 2011.
24 Luce, R. D. and Tukey, J. W., "Simultaneous Conjoint Measurement : A New Type of Fundamental Measurement", Journal of Mathematical Psychology, Vol. 1, No. 1, 1964, pp. 1-27.   DOI
25 Luo, X. R., Warkentin, M. and Li, H., "Understanding technology adoption trade-offs : A conjoint analysis approach", Journal of Computer Information Systems, Vol. 53, No. 3, 2013, pp. 65-74.   DOI
26 Manerikar, V. and Manerikar, S., "A Note on the Use of Conjoint Analysis in Research", Aweshkar Research Journal, Vol. 12, No. 2, 2011, pp. 207-213.
27 McFadden, D., "Measurement of Urban Travel Demand", Journal of Public Economics, Vol. 3, No. 4, 1974, pp. 303-328.   DOI
28 Menon, R. G. V. and Sigurdsson, V., "Conjoint Analysis for Social Media Marketing Experimentation : Choice, Utility Estimates and Preference Ranking", Managerial and Decision Economics, Vol. 37, No. 4-5, 2016, pp. 345-359.   DOI
29 Nikou, S., Bouwman, H., and Reuver, M. D., "A Consumer Perspective on Mobile Service Platforms : A Conjoint Analysis Approach", Communications of the Association for Information Systems, Vol. 34, No. 82, 2014, pp. 1409-1424.
30 Muggah, E. M. and McSweeney, M. B., "Females' attitude and preference for beer : a conjoint analysis study", International Journal of Food Science & Technology, Vol. 52, No. 3, 2017, pp. 808-816.   DOI
31 Okazaki, S. and Mendez, F., "Exploring Convenience in Mobile Commerce : Moderating Effects of Gender", Computers in Human Behaviour, Vol. 29, No. 3, 2013, pp. 1234- 1242.   DOI
32 Payne, C. and Wansink, B., "Quantitative Approaches to Consumer Field Research", Journal of Marketing Theory and Practice, Vol. 19, No. 4, 2011, pp. 377-390.   DOI
33 Orme, B. K., Getting Started with Conjoint Analysis : Strategies for Product Design and Pricing Research, 3rd ed., Research Publishers LLC, Madison, WI, 2013.
34 Pandey, M. and Nakra, N., "Consumer Preference Towards Smartphone Brands, with Special Reference to Android Operating System", Journal of Marketing Management, Vol. 13, No. 4, 2014, pp. 7-22.
35 Park, H.-Y., Shin, G.-C., and Suh, S.-H., "Advantages And Shortcomings Of Korean Chaebols", International Business & Economics Research Journal, Vol. 15, No. 3, 2016, pp. 57-66.
36 Persaud, A. and Azhar, I., "Innovative mobile marketing via smartphones", Marketing Intelligence & Planning, Vol. 30, No. 4, 2012, pp. 418-443.   DOI
37 Reuters, Samsung Shares Plunge to Lowest Level in Weeks after Note 7 Recall, Reuters, 2016, Available at : http://fortune.com/2016/ 09/12/samsung-shares-fall-note-7-recall/ (accessed 20 March 2017).
38 Sawtooth Software., What Can Conjoint Analysis Do For You?, Sawtooth Software, 2013. Available at : https://www.sawtoothsoftware. com/support/videos?id=1361 (accessed 20 August 2017).
39 Baganzi, R. and Lau, A. K. W., "Examining Trust and Risk in Mobile Money Acceptance in Uganda", Sustainability, Vol. 9, No. 12, 2017, pp. 22-33.
40 Sayassatov, D. and Cho, N.-J., "A User Perspective on Smartphone by Using Conjoint", Journal of Information Technology Applications & Management, Vol. 23, No. 3, 2016, pp. 49-59.   DOI
41 Braun, A., Schmeiser, H., and Schreiber, F., "On consumer preferences and the willingness to pay for term life insurance", European Journal of Operational Research, Vol. 253, No. 3, 2016, pp. 761-776.   DOI
42 Brucks, M., Zeithaml, V. A., and Naylor, G., "Price and brand name as indicators of quality dimensions for consumer durables", Journal of Academy of Marketing Science., Vol. 28, No. 3, 2000, pp. 359-374.   DOI
43 Burda, D. and Teuteberg, F., "Exploring consumer preferences in cloud archivinga student's perspective", Behaviour & Information Technology, Vol. 35, No. 2, 2016, pp. 89-105.   DOI
44 Campbell, D. T., Relabelling Internal and External Validity for Applied Social Scientists, Wiley Online Library, 1986, Available at: http://onlinelibrary.wiley.com/doi/10.1002/ ev.1434/pdf (accessed 20 March 2017).
45 Creswell, J., Research Design; Qualitative, Quantitative and Mixed Methods Approach, 3rd ed., SAGE Publications, Inc, Thousand Oaks, CA, 2008.
46 Curry, J., Understanding Conjoint Analysis in 15 Minutes, In Quirk's Marketing Research Review, Orem, UT, 1996.
47 Darley, W. K., Blankson, C., and Luethge, D., "Toward an Integrated Framework for Online Consumer Behaviour and Decision- Making Process : A Review", Psychology & Marketing, Vol. 27, No. 2, 2010, pp. 94-116.   DOI
48 Vriens, M., "Solving marketing problems with conjoint analysis", Journal of Marketing Management, Vol. 10, No. 1-3, 1994, pp. 37-55.   DOI
49 Spralls, S. A., Divine, R. L., and Garver, M. S., "Have the Mobile Coupon Preferences of Millennials Changed?", Journal of Promotion Management, Taylor & Francis, Vol. 22, No. 6, 2016, pp. 792-809.   DOI
50 Statistica., Share of mobile phone users that use a smartphone in South Korea from 2014 to 2019, The Statistics Portal, 2017, Available at : https://www.statista.com/statistics/ 257033/smartphone-user-penetration-in-s outh-korea (accessed 30 November 2017).
51 Walters, C. L., Using Conjoint Analysis to Identify the Determinants of Female Consumers' Online Website Purchase Choices, Northcentral University, 2015, Available at : http://www.sawtoothsoftware.com/acade mics/grants/grant-recipients/242-cbc/1455 -charlene-walters.
52 Wang, C.-H. and Wu, C.-W., "Combining conjoint analysis with Kano model to optimize product varieties of smart phones : a VIKOR perspective", Journal of Industrial and Production Engineering, Vol. 31, No. 4, 2014, pp. 177-186.   DOI
53 Wang, K., Liu, H., Hu, W., and Cox, L., "Using online self-assessment tool to improve conjoint analysis", Internet Research, Vol. 26, No. 3, 2016, pp. 644-660.   DOI
54 Yeh, C.-H., Wang, Y.-S., and Yieh, K., "Predicting smartphone brand loyalty : Consumer value and consumer-brand identification perspectives", International Journal of Information Management, Vol. 36, No. 3, 2016, pp. 245-257.   DOI
55 Yonhap, S., Korea Has 4th Highest Smartphone Penetration : Data, Yonhap, 2015, Available at : http://english.yonhapnews.co. kr/business/2015/07/08/91/0503000000AEN 20150708000700320F.html (accessed 20 March 2017).
56 Desarbo, W. S., Ramaswamy, V., and Cohen, S. H., "Market segmentation with choicebased conjoint analysis", Marketing Letters, Vol. 6, No. 2, 1995, pp. 137-147.   DOI